rm(list=setdiff(ls(), "twd")) 
options(warn=-1)
library(fixest);library(AER);library(stringr);library(knitr)

data<-readRDS(paste(twd,"data/made_data/vreg_wgeos_race.rds",sep=""))


## In person 20
data$in_person_primary_20<-ifelse(data$voting_method_200303 == "P",1,0)
## Abs early 20
data$abs_early_primary_20<-ifelse(data$voting_method_200303 %in% c("A","E"),1,0)
## In person 18
data$in_person_general_18<-ifelse(data$voting_method_181106 == "P",1,0)
## Abs early 18
data$abs_early_general_18<-ifelse(data$voting_method_181106 %in% c("A","E"),1,0)
## Take First Difference
data$diff_in_person<-data$in_person_primary_20-data$in_person_general_18
data$diff_abs_early<-data$abs_early_primary_20-data$abs_early_general_18
### get the minimum of the distance to a consolidated (including super sites)
data$distance_realized_min<-apply(cbind(data$distance_realized,data$distancegov1,data$distancegov2),1,min,na.rm=T)
## Difference between assigned and realized distances (in logs and levels)
data$ln_dist_change<-ifelse(data$moved==1,log(data$distance_realized_min)-log(data$distance_assigned),0)
data$lev_dist_change<-ifelse(data$moved==1,data$distance_realized_min-data$distance_assigned,0)
### Difference between assigned and realized size # of assigned voters (in logs and levels)
data$ln_diff_N<-log(data$realized_N)-log(data$assigned_N)
data$lev_diff_N<-data$realized_N-data$assigned_N

#### Create differences in turnout for all previous elections and run regression ######

## 18-18b

data$in_person_primary_18<-ifelse(data$voting_method_180802== "P",1,0)
data$abs_early_primary_18<-ifelse(data$voting_method_180802 %in% c("A","E"),1,0)

data$diff_in_person_18_18<-data$in_person_general_18-data$in_person_primary_18
data$diff_abs_early_18_18<-data$abs_early_general_18-data$abs_early_primary_18

## 18-16

data$in_person_general_16<-ifelse(data$voting_method_161108== "P",1,0)
data$abs_early_general_16<-ifelse(data$voting_method_161108 %in% c("A","E"),1,0)

data$diff_in_person_18_16<-data$in_person_primary_18-data$in_person_general_16
data$diff_abs_early_18_16<-data$abs_early_primary_18-data$abs_early_general_16

## 16-16a

data$in_person_primary_16a<-ifelse(data$voting_method_160804== "P",1,0)
data$abs_early_primary_16a<-ifelse(data$voting_method_160804 %in% c("A","E"),1,0)

data$diff_in_person_16_16a<-data$in_person_general_16-data$in_person_primary_16a
data$diff_abs_early_16_16a<-data$abs_early_general_16-data$abs_early_primary_16a

## 16a-16b

data$in_person_primary_16b<-ifelse(data$voting_method_160301== "P",1,0)
data$abs_early_primary_16b<-ifelse(data$voting_method_160301 %in% c("A","E"),1,0)


data$diff_in_person_16_16b<-data$in_person_primary_16a-data$in_person_primary_16b
data$diff_abs_early_16_16b<-data$in_person_primary_16a-data$abs_early_primary_16b

## 16b-14

data$in_person_general_14<-ifelse(data$voting_method_141104== "P",1,0)
data$abs_early_general_14<-ifelse(data$voting_method_141104 %in% c("A","E"),1,0)

data$diff_in_person_16_14<-data$in_person_primary_16b-data$in_person_general_14
data$diff_abs_early_16_14<-data$in_person_primary_16b-data$abs_early_general_14

## 14-14a

data$in_person_primary_14<-ifelse(data$voting_method_140807== "P",1,0)
data$abs_early_primary_14<-ifelse(data$voting_method_140807 %in% c("A","E"),1,0)

data$diff_in_person_14_14<-data$in_person_general_14 - data$in_person_primary_14
data$diff_abs_early_14_14<-data$abs_early_general_14 - data$abs_early_primary_14

## 14a-12

data$in_person_general_12<-ifelse(data$voting_method_121106== "P",1,0)
data$abs_early_general_12<-ifelse(data$voting_method_121106 %in% c("A","E"),1,0)

data$diff_in_person_14_12<-data$in_person_primary_14 - data$in_person_general_12
data$diff_abs_early_14_12<-data$abs_early_primary_14 - data$abs_early_general_12



### Create a panel structure (instead of doing first differences)


data_20<-data[,c("text_registrant_id","consolidated","moved","in_person_primary_20", "abs_early_primary_20" ,    
                 "dist_damage_min","dist_power_min",
                 "ln_dist_change",  "ln_diff_N", "polling_place_text_name")
]


data_20$t<-1




data_18<-data[,c("text_registrant_id","consolidated","moved","in_person_general_18", "abs_early_general_18" ,    
                 "dist_damage_min","dist_power_min",
                 "ln_dist_change",  "ln_diff_N","polling_place_text_name")
]


data_18$t<-0


data_18[,c(2:3,6:9)]<-0

names(data_18)<-names(data_20)

data_panel<-rbind(data_18,data_20)

names(data_panel)[names(data_panel) %in% c("in_person_primary_20","abs_early_primary_20")]<-c("in_person","abs_early")


### Conditional Logit
suppressMessages({
clog1<-feglm(in_person ~ consolidated + moved|t + text_registrant_id,data=data_panel,family = binomial(link="logit"),cluster~polling_place_text_name)
clog2<-feglm(in_person ~ consolidated + moved+I(dist_damage_min<500)+I(dist_power_min<500)|t + text_registrant_id,data=data_panel,family = binomial(link="logit"),cluster~polling_place_text_name)
clog3<-feglm(in_person ~ consolidated + moved+ln_dist_change+ln_diff_N+I(dist_damage_min<500)+I(dist_power_min<500)|t + text_registrant_id,data=data_panel,family = binomial(link="logit"),cluster~polling_place_text_name)
clog4<-feglm(in_person ~ consolidated + moved+I(dist_damage_min<500)+I(dist_power_min<500)+abs_early|t + text_registrant_id,data=data_panel,family = binomial(link="logit"),cluster~polling_place_text_name)
clog5<-feglm(in_person ~ consolidated + moved+I(dist_damage_min<500)+I(dist_power_min<500)+ln_dist_change+ln_diff_N+abs_early|t + text_registrant_id,data=data_panel,family = binomial(link="logit"),cluster~polling_place_text_name)
clog6<-feglm(abs_early ~ consolidated + moved|t + text_registrant_id,data=data_panel,family = binomial(link="logit"),cluster~polling_place_text_name)
clog7<-feglm(abs_early ~ consolidated + moved+I(dist_damage_min<500)+I(dist_power_min<500)|t + text_registrant_id,data=data_panel,family = binomial(link="logit"),cluster~polling_place_text_name)
clog8<-feglm(abs_early ~ consolidated + moved+ln_dist_change+ln_diff_N+I(dist_damage_min<500)+I(dist_power_min<500)|t + text_registrant_id,data=data_panel,family = binomial(link="logit"),cluster~polling_place_text_name)
})

log_print(
  esttex(list(clog1,clog2,clog3,clog4,clog5,clog6,clog7,clog8),
       coefstat = "confint",signif.code = NA, 
       keep = c("moved","consolidated","ln_dist_change","ln_diff_N"),
       fitstat = c("n")
       )
)
